Google senior AI product manager Shubham Saboo has turned one of the thorniest problems in agent design into an open-source engineering exercise: persistent memory. This week, he published an ...
NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — ...
Retrieval-augmented generation enhances the performance of AI agents by expanding their recall. It can do this in three ...
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I tested my local LLM across 4 different tools, and only one actually unleashed its potential
If you're like me and not particularly comfortable with spinning up CLI tools, or if you're perhaps new to self-hosting LLMs, then chances are your default runner is LM Studio. It's been my default ...
Large language models (LLMs) aren’t actually giant computer brains. Instead, they are massive vector spaces in which the probabilities of tokens occurring in a specific order is encoded. Billions of ...
If we want to avoid making AI agents a huge new attack surface, we’ve got to treat agent memory the way we treat databases: with firewalls, audits, and access privileges. The pace at which large ...
A new technical paper, “Rethinking Compute Substrates for 3D-Stacked Near-Memory LLM Decoding: Microarchitecture-Scheduling Co-Design,” was published by researchers at University of Edinburgh, Peking ...
“The rapid growth of LLMs has revolutionized natural language processing and AI analysis, but their increasing size and memory demands present significant challenges. A common solution is to spill ...
A little over a year after it upended the tech industry, DeepSeek is back with another apparent breakthrough: a means to stop current large language models (LLMs) from wasting computational depth on ...
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